Overview

Brought to you by YData

Dataset statistics

Number of variables16
Number of observations52413
Missing cells116133
Missing cells (%)13.8%
Duplicate rows1051
Duplicate rows (%)2.0%
Total size in memory8.8 MiB
Average record size in memory176.3 B

Variable types

Numeric15
Categorical1

Alerts

Dataset has 1051 (2.0%) duplicate rowsDuplicates
13172_FERM0101.PUMP_1_PV is highly imbalanced (99.9%)Imbalance
13172_FERM0101.Agitation_PV has 4327 (8.3%) missing valuesMissing
13172_FERM0101.Air_Sparge_PV has 4327 (8.3%) missing valuesMissing
13172_FERM0101.Biocontainer_Pressure_PV has 4326 (8.3%) missing valuesMissing
13172_FERM0101.DO_1_PV has 51235 (97.8%) missing valuesMissing
13172_FERM0101.DO_2_PV has 4327 (8.3%) missing valuesMissing
13172_FERM0101.Gas_Overlay_PV has 4327 (8.3%) missing valuesMissing
13172_FERM0101.Load_Cell_Net_PV has 4326 (8.3%) missing valuesMissing
13172_FERM0101.pH_1_PV has 4326 (8.3%) missing valuesMissing
13172_FERM0101.pH_2_PV has 4326 (8.3%) missing valuesMissing
13172_FERM0101.PUMP_1_PV has 4327 (8.3%) missing valuesMissing
13172_FERM0101.PUMP_1_TOTAL has 4326 (8.3%) missing valuesMissing
13172_FERM0101.PUMP_2_PV has 4327 (8.3%) missing valuesMissing
13172_FERM0101.PUMP_2_TOTAL has 4326 (8.3%) missing valuesMissing
13172_FERM0101.Single_Use_DO_PV has 4327 (8.3%) missing valuesMissing
13172_FERM0101.Single_Use_pH_PV has 4327 (8.3%) missing valuesMissing
13172_FERM0101.Temperatura_PV has 4326 (8.3%) missing valuesMissing
13172_FERM0101.PUMP_2_PV is highly skewed (γ1 = 78.03242767)Skewed
13172_FERM0101.Agitation_PV has 23681 (45.2%) zerosZeros
13172_FERM0101.Air_Sparge_PV has 47067 (89.8%) zerosZeros
13172_FERM0101.DO_1_PV has 1079 (2.1%) zerosZeros
13172_FERM0101.DO_2_PV has 43000 (82.0%) zerosZeros
13172_FERM0101.Gas_Overlay_PV has 18869 (36.0%) zerosZeros
13172_FERM0101.PUMP_1_TOTAL has 7505 (14.3%) zerosZeros
13172_FERM0101.PUMP_2_PV has 47762 (91.1%) zerosZeros
13172_FERM0101.PUMP_2_TOTAL has 28873 (55.1%) zerosZeros

Reproduction

Analysis started2024-09-29 18:18:32.159327
Analysis finished2024-09-29 18:18:50.074583
Duration17.92 seconds
Software versionydata-profiling v0.0.dev0
Download configurationconfig.json

Variables

13172_FERM0101.Agitation_PV
Real number (ℝ)

MISSING  ZEROS 

Distinct368
Distinct (%)0.8%
Missing4327
Missing (%)8.3%
Infinite0
Infinite (%)0.0%
Mean21.470704
Minimum0
Maximum80
Zeros23681
Zeros (%)45.2%
Negative0
Negative (%)0.0%
Memory size2.8 MiB
2024-09-29T20:18:50.125448image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median20
Q334.504001
95-th percentile72
Maximum80
Range80
Interquartile range (IQR)34.504001

Descriptive statistics

Standard deviation27.278393
Coefficient of variation (CV)1.2704936
Kurtosis-0.49312504
Mean21.470704
Median Absolute Deviation (MAD)20
Skewness1.0155072
Sum1032440.3
Variance744.11072
MonotonicityNot monotonic
2024-09-29T20:18:50.204578image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 23681
45.2%
20 12093
23.1%
72 8368
 
16.0%
44 1995
 
3.8%
36 476
 
0.9%
80 443
 
0.8%
40 193
 
0.4%
48 188
 
0.4%
34.16799927 22
 
< 0.1%
34.50400085 21
 
< 0.1%
Other values (358) 606
 
1.2%
(Missing) 4327
 
8.3%
ValueCountFrequency (%)
0 23681
45.2%
20 12093
23.1%
20.03462422 1
 
< 0.1%
20.21952767 1
 
< 0.1%
20.32444191 1
 
< 0.1%
20.47311166 1
 
< 0.1%
20.61295716 1
 
< 0.1%
20.90212257 1
 
< 0.1%
21.19083002 1
 
< 0.1%
21.29648179 1
 
< 0.1%
ValueCountFrequency (%)
80 443
 
0.8%
72 8368
16.0%
71.9999939 1
 
< 0.1%
71.99992676 1
 
< 0.1%
71.99986247 1
 
< 0.1%
71.99979858 1
 
< 0.1%
71.99973145 1
 
< 0.1%
71.99966714 1
 
< 0.1%
71.99960327 1
 
< 0.1%
71.99953901 1
 
< 0.1%

13172_FERM0101.Air_Sparge_PV
Real number (ℝ)

MISSING  ZEROS 

Distinct1020
Distinct (%)2.1%
Missing4327
Missing (%)8.3%
Infinite0
Infinite (%)0.0%
Mean0.1610792
Minimum0
Maximum16.002144
Zeros47067
Zeros (%)89.8%
Negative0
Negative (%)0.0%
Memory size2.8 MiB
2024-09-29T20:18:50.277729image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum16.002144
Range16.002144
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.3927367
Coefficient of variation (CV)8.6462853
Kurtosis98.371512
Mean0.1610792
Median Absolute Deviation (MAD)0
Skewness9.7372634
Sum7745.6542
Variance1.9397155
MonotonicityNot monotonic
2024-09-29T20:18:50.350897image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 47067
89.8%
15.96247623 1
 
< 0.1%
9.905471039 1
 
< 0.1%
0.001870622385 1
 
< 0.1%
1.926111162 1
 
< 0.1%
3.488108063 1
 
< 0.1%
7.761153412 1
 
< 0.1%
0.8016670227 1
 
< 0.1%
3.465966537 1
 
< 0.1%
9.821643829 1
 
< 0.1%
Other values (1010) 1010
 
1.9%
(Missing) 4327
 
8.3%
ValueCountFrequency (%)
0 47067
89.8%
0.0001293366145 1
 
< 0.1%
0.0004012896147 1
 
< 0.1%
0.0006448696044 1
 
< 0.1%
0.001870622385 1
 
< 0.1%
0.00254522155 1
 
< 0.1%
0.003967829603 1
 
< 0.1%
0.004921793255 1
 
< 0.1%
0.009285172965 1
 
< 0.1%
0.06251979904 1
 
< 0.1%
ValueCountFrequency (%)
16.00214408 1
< 0.1%
16.0019909 1
< 0.1%
16.00197933 1
< 0.1%
16.00157261 1
< 0.1%
16.0014496 1
< 0.1%
16.00119973 1
< 0.1%
16.00102334 1
< 0.1%
16.00085492 1
< 0.1%
16.00080857 1
< 0.1%
16.00078666 1
< 0.1%

13172_FERM0101.Biocontainer_Pressure_PV
Real number (ℝ)

MISSING 

Distinct23793
Distinct (%)49.5%
Missing4326
Missing (%)8.3%
Infinite0
Infinite (%)0.0%
Mean167.96129
Minimum-12.795142
Maximum480
Zeros96
Zeros (%)0.2%
Negative18162
Negative (%)34.7%
Memory size2.8 MiB
2024-09-29T20:18:50.425876image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Quantile statistics

Minimum-12.795142
5-th percentile-4.8958313
Q1-1.0069458
median1.5127144
Q3480
95-th percentile480
Maximum480
Range492.79514
Interquartile range (IQR)481.00695

Descriptive statistics

Standard deviation229.24036
Coefficient of variation (CV)1.3648404
Kurtosis-1.6072484
Mean167.96129
Median Absolute Deviation (MAD)3.3044391
Skewness0.62627594
Sum8076754.5
Variance52551.142
MonotonicityNot monotonic
2024-09-29T20:18:50.499150image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
480 16854
32.2%
-0.6018493652 129
 
0.2%
-0.5815979004 129
 
0.2%
-1.25 128
 
0.2%
-1.290509033 113
 
0.2%
-1.027197266 112
 
0.2%
-0.8246520996 111
 
0.2%
-1.067706299 110
 
0.2%
-1.513311768 109
 
0.2%
-0.7841430664 103
 
0.2%
Other values (23783) 30189
57.6%
(Missing) 4326
 
8.3%
ValueCountFrequency (%)
-12.7951416 1
< 0.1%
-12.78697677 1
< 0.1%
-12.76347502 1
< 0.1%
-12.76179238 1
< 0.1%
-12.75463257 1
< 0.1%
-12.74172747 1
< 0.1%
-12.72316363 1
< 0.1%
-12.70664826 1
< 0.1%
-12.5520813 1
< 0.1%
-12.51962912 1
< 0.1%
ValueCountFrequency (%)
480 16854
32.2%
237.2890227 1
 
< 0.1%
127.6138047 1
 
< 0.1%
10.234375 1
 
< 0.1%
10.17036768 1
 
< 0.1%
9.714243726 1
 
< 0.1%
9.687439282 1
 
< 0.1%
9.509005687 1
 
< 0.1%
8.965247104 1
 
< 0.1%
8.801130856 1
 
< 0.1%

13172_FERM0101.DO_1_PV
Real number (ℝ)

MISSING  ZEROS 

Distinct65
Distinct (%)5.5%
Missing51235
Missing (%)97.8%
Infinite0
Infinite (%)0.0%
Mean1.8817048
Minimum0
Maximum78.602374
Zeros1079
Zeros (%)2.1%
Negative0
Negative (%)0.0%
Memory size2.8 MiB
2024-09-29T20:18:50.570827image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile16.256535
Maximum78.602374
Range78.602374
Interquartile range (IQR)0

Descriptive statistics

Standard deviation7.5407762
Coefficient of variation (CV)4.0074172
Kurtosis41.055316
Mean1.8817048
Median Absolute Deviation (MAD)0
Skewness5.7636799
Sum2216.6482
Variance56.863305
MonotonicityNot monotonic
2024-09-29T20:18:50.645488image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1079
 
2.1%
16.50939484 10
 
< 0.1%
17.0197113 5
 
< 0.1%
16.63812408 4
 
< 0.1%
15.6266861 4
 
< 0.1%
15.36923065 4
 
< 0.1%
14.35319672 3
 
< 0.1%
16.25653534 3
 
< 0.1%
16.76685181 3
 
< 0.1%
14.22446899 2
 
< 0.1%
Other values (55) 61
 
0.1%
(Missing) 51235
97.8%
ValueCountFrequency (%)
0 1079
2.1%
11.97767081 1
 
< 0.1%
13.08430481 2
 
< 0.1%
13.46589203 1
 
< 0.1%
13.50423889 1
 
< 0.1%
14.09574127 1
 
< 0.1%
14.22446899 2
 
< 0.1%
14.26213692 1
 
< 0.1%
14.31314325 1
 
< 0.1%
14.35319672 3
 
< 0.1%
ValueCountFrequency (%)
78.60237427 1
< 0.1%
75.55427246 1
< 0.1%
69.58220215 1
< 0.1%
66.02838745 1
< 0.1%
62.98027954 1
< 0.1%
58.78742065 1
< 0.1%
55.6105957 1
< 0.1%
52.82169661 1
< 0.1%
50.02930603 1
< 0.1%
46.72375183 1
< 0.1%

13172_FERM0101.DO_2_PV
Real number (ℝ)

MISSING  ZEROS 

Distinct3989
Distinct (%)8.3%
Missing4327
Missing (%)8.3%
Infinite0
Infinite (%)0.0%
Mean3.2957988
Minimum0
Maximum89.337708
Zeros43000
Zeros (%)82.0%
Negative0
Negative (%)0.0%
Memory size2.8 MiB
2024-09-29T20:18:50.720618image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile20.78866
Maximum89.337708
Range89.337708
Interquartile range (IQR)0

Descriptive statistics

Standard deviation11.82504
Coefficient of variation (CV)3.5879131
Kurtosis21.949387
Mean3.2957988
Median Absolute Deviation (MAD)0
Skewness4.5223128
Sum158481.78
Variance139.83157
MonotonicityNot monotonic
2024-09-29T20:18:50.789686image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 43000
82.0%
78.38275757 20
 
< 0.1%
79.12711792 15
 
< 0.1%
78.82723389 13
 
< 0.1%
28.45993042 12
 
< 0.1%
78.68264771 12
 
< 0.1%
78.23817139 12
 
< 0.1%
78.08822632 11
 
< 0.1%
16.59084625 11
 
< 0.1%
16.46363831 10
 
< 0.1%
Other values (3979) 4970
 
9.5%
(Missing) 4327
 
8.3%
ValueCountFrequency (%)
0 43000
82.0%
0.2953654612 1
 
< 0.1%
2.127795792 1
 
< 0.1%
2.13805027 2
 
< 0.1%
3.37597847 2
 
< 0.1%
3.553162766 1
 
< 0.1%
3.579579544 2
 
< 0.1%
3.883299637 1
 
< 0.1%
3.931254196 1
 
< 0.1%
3.980663681 1
 
< 0.1%
ValueCountFrequency (%)
89.33770752 1
 
< 0.1%
88.82005455 1
 
< 0.1%
88.64082885 1
 
< 0.1%
88.36628418 1
 
< 0.1%
88.10524316 1
 
< 0.1%
87.69441528 3
< 0.1%
87.60070801 1
 
< 0.1%
87.54655151 1
 
< 0.1%
87.09644165 1
 
< 0.1%
86.69011841 1
 
< 0.1%

13172_FERM0101.Gas_Overlay_PV
Real number (ℝ)

MISSING  ZEROS 

Distinct29216
Distinct (%)60.8%
Missing4327
Missing (%)8.3%
Infinite0
Infinite (%)0.0%
Mean2.4341266
Minimum0
Maximum16.001288
Zeros18869
Zeros (%)36.0%
Negative0
Negative (%)0.0%
Memory size2.8 MiB
2024-09-29T20:18:50.857032image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3.999765
Q34.0000574
95-th percentile4.0003529
Maximum16.001288
Range16.001288
Interquartile range (IQR)4.0000574

Descriptive statistics

Standard deviation1.964264
Coefficient of variation (CV)0.8069687
Kurtosis-1.4339886
Mean2.4341266
Median Absolute Deviation (MAD)0.00047311094
Skewness-0.37453336
Sum117047.41
Variance3.8583329
MonotonicityNot monotonic
2024-09-29T20:18:50.931684image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 18869
36.0%
3.999869537 2
 
< 0.1%
4.000040054 2
 
< 0.1%
3.999709901 1
 
< 0.1%
4.000009576 1
 
< 0.1%
3.999959469 1
 
< 0.1%
3.999456783 1
 
< 0.1%
3.999471804 1
 
< 0.1%
4.000089511 1
 
< 0.1%
3.999497137 1
 
< 0.1%
Other values (29206) 29206
55.7%
(Missing) 4327
 
8.3%
ValueCountFrequency (%)
0 18869
36.0%
1.783709784 1
 
< 0.1%
2.549639423 1
 
< 0.1%
3.097292725 1
 
< 0.1%
3.100984381 1
 
< 0.1%
3.120230417 1
 
< 0.1%
3.307985819 1
 
< 0.1%
3.713406845 1
 
< 0.1%
3.773994963 1
 
< 0.1%
3.845119435 1
 
< 0.1%
ValueCountFrequency (%)
16.00128796 1
< 0.1%
16.00103624 1
< 0.1%
16.0006285 1
< 0.1%
16.00056073 1
< 0.1%
16.00045408 1
< 0.1%
15.99913849 1
< 0.1%
15.99895403 1
< 0.1%
12.89630894 1
< 0.1%
12.6673534 1
< 0.1%
10.35791138 1
< 0.1%

13172_FERM0101.Load_Cell_Net_PV
Real number (ℝ)

MISSING 

Distinct2950
Distinct (%)6.1%
Missing4326
Missing (%)8.3%
Infinite0
Infinite (%)0.0%
Mean70.357556
Minimum-8.4796569
Maximum175.50066
Zeros394
Zeros (%)0.8%
Negative19514
Negative (%)37.2%
Memory size2.8 MiB
2024-09-29T20:18:51.005800image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Quantile statistics

Minimum-8.4796569
5-th percentile-6.9599998
Q1-6.1599998
median79.2
Q3160.4
95-th percentile166.24
Maximum175.50066
Range183.98032
Interquartile range (IQR)166.56

Descriptive statistics

Standard deviation77.132751
Coefficient of variation (CV)1.0962966
Kurtosis-1.8172078
Mean70.357556
Median Absolute Deviation (MAD)82.115153
Skewness0.18140837
Sum3383283.8
Variance5949.4612
MonotonicityNot monotonic
2024-09-29T20:18:51.078744image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-6.959999847 3219
 
6.1%
-5.920000076 1904
 
3.6%
-6 1029
 
2.0%
-7.040000153 800
 
1.5%
-6.719999695 737
 
1.4%
-6.8 659
 
1.3%
-6.240000153 656
 
1.3%
-6.879999542 649
 
1.2%
-7.2 606
 
1.2%
161.3599976 560
 
1.1%
Other values (2940) 37268
71.1%
(Missing) 4326
 
8.3%
ValueCountFrequency (%)
-8.479656912 1
 
< 0.1%
-8.319999695 1
 
< 0.1%
-8.240000153 1
 
< 0.1%
-8.159999847 2
 
< 0.1%
-8.080000305 1
 
< 0.1%
-8.079999542 1
 
< 0.1%
-8 2
 
< 0.1%
-7.919999695 9
< 0.1%
-7.855802566 1
 
< 0.1%
-7.840000153 11
< 0.1%
ValueCountFrequency (%)
175.5006581 1
< 0.1%
175.370362 1
< 0.1%
175.2 1
< 0.1%
175.0974667 1
< 0.1%
174.9340775 1
< 0.1%
174.4536506 1
< 0.1%
174.280661 1
< 0.1%
174 1
< 0.1%
173.3169947 1
< 0.1%
173.1071261 1
< 0.1%

13172_FERM0101.pH_1_PV
Real number (ℝ)

MISSING 

Distinct5905
Distinct (%)12.3%
Missing4326
Missing (%)8.3%
Infinite0
Infinite (%)0.0%
Mean-0.55715161
Minimum-4.7790901
Maximum9.6652878
Zeros12
Zeros (%)< 0.1%
Negative23181
Negative (%)44.2%
Memory size2.8 MiB
2024-09-29T20:18:51.155083image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Quantile statistics

Minimum-4.7790901
5-th percentile-4.6862289
Q1-4.6862289
median1.4021345
Q31.7693521
95-th percentile5.9916756
Maximum9.6652878
Range14.444378
Interquartile range (IQR)6.4555811

Descriptive statistics

Standard deviation4.1954752
Coefficient of variation (CV)-7.5302217
Kurtosis-1.5230549
Mean-0.55715161
Median Absolute Deviation (MAD)4.6926088
Skewness0.26395314
Sum-26791.749
Variance17.602012
MonotonicityNot monotonic
2024-09-29T20:18:51.226854image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-4.686228943 22828
43.6%
1.536162758 2842
 
5.4%
1.502809715 1144
 
2.2%
1.579955292 751
 
1.4%
1.694073105 720
 
1.4%
1.76935215 691
 
1.3%
1.746356583 671
 
1.3%
1.714764023 602
 
1.1%
1.507031631 463
 
0.9%
1.501964569 452
 
0.9%
Other values (5895) 16923
32.3%
(Missing) 4326
 
8.3%
ValueCountFrequency (%)
-4.779090118 1
 
< 0.1%
-4.686228943 22828
43.6%
-4.684416789 1
 
< 0.1%
-4.683779182 1
 
< 0.1%
-4.683502806 1
 
< 0.1%
-4.683336452 1
 
< 0.1%
-4.681602549 1
 
< 0.1%
-4.680866583 1
 
< 0.1%
-4.680287397 1
 
< 0.1%
-4.679195669 1
 
< 0.1%
ValueCountFrequency (%)
9.665287781 2
< 0.1%
9.53779068 1
< 0.1%
8.979374274 1
< 0.1%
8.381080236 1
< 0.1%
8.378705559 1
< 0.1%
8.103669818 1
< 0.1%
7.39616593 1
< 0.1%
7.055183028 1
< 0.1%
7.038299496 1
< 0.1%
7.038153495 1
< 0.1%

13172_FERM0101.pH_2_PV
Real number (ℝ)

MISSING 

Distinct5051
Distinct (%)10.5%
Missing4326
Missing (%)8.3%
Infinite0
Infinite (%)0.0%
Mean1.2278078
Minimum-0.8517828
Maximum10.041967
Zeros26
Zeros (%)< 0.1%
Negative24964
Negative (%)47.6%
Memory size2.8 MiB
2024-09-29T20:18:51.300034image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Quantile statistics

Minimum-0.8517828
5-th percentile-0.8517828
Q1-0.8517828
median-0.61330414
Q31.8767929
95-th percentile6.0853622
Maximum10.041967
Range10.89375
Interquartile range (IQR)2.7285757

Descriptive statistics

Standard deviation2.5929226
Coefficient of variation (CV)2.1118311
Kurtosis-0.64973699
Mean1.2278078
Median Absolute Deviation (MAD)0.23847866
Skewness0.9494498
Sum59041.592
Variance6.7232476
MonotonicityNot monotonic
2024-09-29T20:18:51.371682image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-0.8517827988 19006
36.3%
-0.6520252228 4535
 
8.7%
1.298497772 2000
 
3.8%
-0.6133041382 1397
 
2.7%
1.374933434 692
 
1.3%
1.340048027 678
 
1.3%
1.063763046 657
 
1.3%
1.366745186 585
 
1.1%
1.407578659 569
 
1.1%
1.211921883 554
 
1.1%
Other values (5041) 17414
33.2%
(Missing) 4326
 
8.3%
ValueCountFrequency (%)
-0.8517827988 19006
36.3%
-0.8413989786 1
 
< 0.1%
-0.8402301598 1
 
< 0.1%
-0.8309171953 1
 
< 0.1%
-0.6775653715 1
 
< 0.1%
-0.6520252228 4535
 
8.7%
-0.6133041382 1397
 
2.7%
-0.4635412804 1
 
< 0.1%
-0.4579264472 1
 
< 0.1%
-0.4475497566 1
 
< 0.1%
ValueCountFrequency (%)
10.04196701 1
 
< 0.1%
7.72420945 1
 
< 0.1%
7.516550345 1
 
< 0.1%
7.277795215 1
 
< 0.1%
7.160340881 1
 
< 0.1%
6.824984513 1
 
< 0.1%
6.70579071 1
 
< 0.1%
6.636557171 1
 
< 0.1%
6.478161621 14
< 0.1%
6.478126665 1
 
< 0.1%

13172_FERM0101.PUMP_1_PV
Categorical

IMBALANCE  MISSING 

Distinct2
Distinct (%)< 0.1%
Missing4327
Missing (%)8.3%
Memory size2.8 MiB
0.0
48084 
48.0
 
2

Length

Max length4
Median length3
Mean length3.0000416
Min length3

Characters and Unicode

Total characters144260
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 48084
91.7%
48.0 2
 
< 0.1%
(Missing) 4327
 
8.3%

Length

2024-09-29T20:18:51.437946image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-09-29T20:18:51.486740image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
ValueCountFrequency (%)
0.0 48084
> 99.9%
48.0 2
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 96170
66.7%
. 48086
33.3%
4 2
 
< 0.1%
8 2
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 144260
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 96170
66.7%
. 48086
33.3%
4 2
 
< 0.1%
8 2
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 144260
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 96170
66.7%
. 48086
33.3%
4 2
 
< 0.1%
8 2
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 144260
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 96170
66.7%
. 48086
33.3%
4 2
 
< 0.1%
8 2
 
< 0.1%

13172_FERM0101.PUMP_1_TOTAL
Real number (ℝ)

MISSING  ZEROS 

Distinct174
Distinct (%)0.4%
Missing4326
Missing (%)8.3%
Infinite0
Infinite (%)0.0%
Mean11.264756
Minimum0
Maximum111.59999
Zeros7505
Zeros (%)14.3%
Negative0
Negative (%)0.0%
Memory size2.8 MiB
2024-09-29T20:18:51.544325image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q14.9599998
median7.4399994
Q312.4
95-th percentile44.63999
Maximum111.59999
Range111.59999
Interquartile range (IQR)7.4400002

Descriptive statistics

Standard deviation12.879822
Coefficient of variation (CV)1.1433734
Kurtosis12.032343
Mean11.264756
Median Absolute Deviation (MAD)2.4800003
Skewness2.8694704
Sum541688.31
Variance165.88981
MonotonicityNot monotonic
2024-09-29T20:18:51.614120image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7.43999939 10885
20.8%
9.919999695 7976
15.2%
0 7505
14.3%
4.959999847 5299
10.1%
12.4 4015
 
7.7%
44.63999023 3733
 
7.1%
17.36000061 2729
 
5.2%
2.479999924 1592
 
3.0%
4.959999084 886
 
1.7%
22.32000122 817
 
1.6%
Other values (164) 2650
 
5.1%
(Missing) 4326
 
8.3%
ValueCountFrequency (%)
0 7505
14.3%
0.002796132197 1
 
< 0.1%
0.02643525577 1
 
< 0.1%
0.06826814326 1
 
< 0.1%
0.07411262712 1
 
< 0.1%
0.08958652972 1
 
< 0.1%
0.1360892628 1
 
< 0.1%
0.1401083653 1
 
< 0.1%
0.1511936223 1
 
< 0.1%
0.1669230632 1
 
< 0.1%
ValueCountFrequency (%)
111.5999878 74
 
0.1%
104.5733643 74
 
0.1%
91.75997314 4
 
< 0.1%
84.31997681 1
 
< 0.1%
76.87998047 86
 
0.2%
69.43998413 1
 
< 0.1%
66.95998535 1
 
< 0.1%
61.99998779 1
 
< 0.1%
47.11999207 68
 
0.1%
44.63999023 3733
7.1%

13172_FERM0101.PUMP_2_PV
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct310
Distinct (%)0.6%
Missing4327
Missing (%)8.3%
Infinite0
Infinite (%)0.0%
Mean0.017902191
Minimum0
Maximum48
Zeros47762
Zeros (%)91.1%
Negative0
Negative (%)0.0%
Memory size2.8 MiB
2024-09-29T20:18:51.685781image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum48
Range48
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.49467443
Coefficient of variation (CV)27.632061
Kurtosis7385.4548
Mean0.017902191
Median Absolute Deviation (MAD)0
Skewness78.032428
Sum860.84474
Variance0.24470279
MonotonicityNot monotonic
2024-09-29T20:18:51.759084image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 47762
91.1%
8 6
 
< 0.1%
1.742733408 4
 
< 0.1%
4.799926758 4
 
< 0.1%
48 4
 
< 0.1%
2.399963379 2
 
< 0.1%
3.136338436 1
 
< 0.1%
3.668730086 1
 
< 0.1%
0.5859408074 1
 
< 0.1%
0.2370310548 1
 
< 0.1%
Other values (300) 300
 
0.6%
(Missing) 4327
 
8.3%
ValueCountFrequency (%)
0 47762
91.1%
2.930807446 × 10-51
 
< 0.1%
0.001160210595 1
 
< 0.1%
0.001382299297 1
 
< 0.1%
0.004210924582 1
 
< 0.1%
0.004791641235 1
 
< 0.1%
0.007827220814 1
 
< 0.1%
0.008307240502 1
 
< 0.1%
0.01150828542 1
 
< 0.1%
0.01800439949 1
 
< 0.1%
ValueCountFrequency (%)
48 4
< 0.1%
8 6
< 0.1%
7.734632664 1
 
< 0.1%
7.199890137 1
 
< 0.1%
6.962828807 1
 
< 0.1%
6.76271029 1
 
< 0.1%
6.460059839 1
 
< 0.1%
6.419834763 1
 
< 0.1%
6.293432236 1
 
< 0.1%
5.776636972 1
 
< 0.1%

13172_FERM0101.PUMP_2_TOTAL
Real number (ℝ)

MISSING  ZEROS 

Distinct282
Distinct (%)0.6%
Missing4326
Missing (%)8.3%
Infinite0
Infinite (%)0.0%
Mean18.354265
Minimum0
Maximum1082.1447
Zeros28873
Zeros (%)55.1%
Negative0
Negative (%)0.0%
Memory size2.8 MiB
2024-09-29T20:18:51.830623image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q312.835783
95-th percentile47.635233
Maximum1082.1447
Range1082.1447
Interquartile range (IQR)12.835783

Descriptive statistics

Standard deviation78.606721
Coefficient of variation (CV)4.2827495
Kurtosis50.7141
Mean18.354265
Median Absolute Deviation (MAD)0
Skewness6.9786517
Sum882601.55
Variance6179.0165
MonotonicityNot monotonic
2024-09-29T20:18:51.901867image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 28873
55.1%
14.3049881 3726
 
7.1%
2.766121483 2190
 
4.2%
21.62820587 1251
 
2.4%
6.069880295 949
 
1.8%
36.84609985 884
 
1.7%
5.523295975 875
 
1.7%
9.484403992 852
 
1.6%
570.0592285 768
 
1.5%
12.83578339 713
 
1.4%
Other values (272) 7006
 
13.4%
(Missing) 4326
 
8.3%
ValueCountFrequency (%)
0 28873
55.1%
0.01666003704 1
 
< 0.1%
0.0167649371 1
 
< 0.1%
0.01684833063 1
 
< 0.1%
0.0715862416 1
 
< 0.1%
0.08394892034 1
 
< 0.1%
0.08654680633 1
 
< 0.1%
0.125176948 1
 
< 0.1%
0.1873602335 1
 
< 0.1%
0.1948790784 1
 
< 0.1%
ValueCountFrequency (%)
1082.144727 12
 
< 0.1%
1052.611908 1
 
< 0.1%
824.7780428 1
 
< 0.1%
651.8535156 50
 
0.1%
632.4105591 1
 
< 0.1%
611.8286621 3
 
< 0.1%
596.9721187 1
 
< 0.1%
574.037207 3
 
< 0.1%
570.0592285 768
1.5%
559.6328125 1
 
< 0.1%

13172_FERM0101.Single_Use_DO_PV
Real number (ℝ)

MISSING 

Distinct6106
Distinct (%)12.7%
Missing4327
Missing (%)8.3%
Infinite0
Infinite (%)0.0%
Mean690.827
Minimum0
Maximum875.36055
Zeros9
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size2.8 MiB
2024-09-29T20:18:51.972585image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile18.489357
Q1736.84443
median799.99199
Q3799.99199
95-th percentile817.15215
Maximum875.36055
Range875.36055
Interquartile range (IQR)63.147559

Descriptive statistics

Standard deviation254.61141
Coefficient of variation (CV)0.36856031
Kurtosis2.7498305
Mean690.827
Median Absolute Deviation (MAD)0
Skewness-2.1422047
Sum33219107
Variance64826.971
MonotonicityNot monotonic
2024-09-29T20:18:52.042218image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
799.9919922 26192
50.0%
809.7084961 3731
 
7.1%
736.8444336 2019
 
3.9%
827.9775391 772
 
1.5%
730.9868164 766
 
1.5%
757.1379883 754
 
1.4%
875.3605469 750
 
1.4%
605.275 692
 
1.3%
727.7947754 689
 
1.3%
718.2546387 616
 
1.2%
Other values (6096) 11105
21.2%
(Missing) 4327
 
8.3%
ValueCountFrequency (%)
0 9
< 0.1%
0.558311291 1
 
< 0.1%
0.8720000267 1
 
< 0.1%
0.8783016688 1
 
< 0.1%
0.8800000191 1
 
< 0.1%
0.8846777564 1
 
< 0.1%
0.8863550276 1
 
< 0.1%
0.8896752112 1
 
< 0.1%
0.9023908683 1
 
< 0.1%
0.9039999962 2
 
< 0.1%
ValueCountFrequency (%)
875.3605469 750
 
1.4%
871.5458984 34
 
0.1%
850.8743164 46
 
0.1%
840.2395508 123
 
0.2%
827.9775391 772
 
1.5%
826.3526367 116
 
0.2%
825.159375 118
 
0.2%
817.1521484 610
 
1.2%
810.7552998 1
 
< 0.1%
809.7084961 3731
7.1%

13172_FERM0101.Single_Use_pH_PV
Real number (ℝ)

MISSING 

Distinct1214
Distinct (%)2.5%
Missing4327
Missing (%)8.3%
Infinite0
Infinite (%)0.0%
Mean677.10959
Minimum-794.048
Maximum800.73599
Zeros1
Zeros (%)< 0.1%
Negative229
Negative (%)0.4%
Memory size2.8 MiB
2024-09-29T20:18:52.107801image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Quantile statistics

Minimum-794.048
5-th percentile5.9439941
Q1799.93599
median800.16797
Q3800.36797
95-th percentile800.47998
Maximum800.73599
Range1594.784
Interquartile range (IQR)0.43198242

Descriptive statistics

Standard deviation297.37499
Coefficient of variation (CV)0.43918296
Kurtosis3.5208656
Mean677.10959
Median Absolute Deviation (MAD)0.20795898
Skewness-2.166554
Sum32559492
Variance88431.887
MonotonicityNot monotonic
2024-09-29T20:18:52.182433image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
800.447998 4177
 
8.0%
800.2080078 3429
 
6.5%
799.8799805 2418
 
4.6%
800.2959961 1815
 
3.5%
800.4799805 1804
 
3.4%
800.3040039 1695
 
3.2%
800.3679688 1677
 
3.2%
800.2160156 1646
 
3.1%
800.0959961 1318
 
2.5%
800.3919922 1268
 
2.4%
Other values (1204) 26839
51.2%
(Missing) 4327
 
8.3%
ValueCountFrequency (%)
-794.047998 1
< 0.1%
-793.8640137 2
< 0.1%
-788.6320313 2
< 0.1%
-788.6080078 1
< 0.1%
-788.5760254 1
< 0.1%
-788.552002 1
< 0.1%
-788.5360352 1
< 0.1%
-788.5120117 1
< 0.1%
-788.4800293 1
< 0.1%
-788.4720215 1
< 0.1%
ValueCountFrequency (%)
800.7359863 817
 
1.6%
800.6 1242
 
2.4%
800.4799805 1804
3.4%
800.447998 4177
8.0%
800.4319824 656
 
1.3%
800.4 520
 
1.0%
800.3919922 1268
 
2.4%
800.3679688 1677
3.2%
800.3199707 1242
 
2.4%
800.3040039 1695
3.2%

13172_FERM0101.Temperatura_PV
Real number (ℝ)

MISSING 

Distinct27370
Distinct (%)56.9%
Missing4326
Missing (%)8.3%
Infinite0
Infinite (%)0.0%
Mean16.279289
Minimum0
Maximum80.999279
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size2.8 MiB
2024-09-29T20:18:52.257039image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3.247998
Q110.456031
median16.471997
Q320.75313
95-th percentile29.667737
Maximum80.999279
Range80.999279
Interquartile range (IQR)10.297099

Descriptive statistics

Standard deviation8.6351792
Coefficient of variation (CV)0.53043959
Kurtosis-0.81387714
Mean16.279289
Median Absolute Deviation (MAD)5.576001
Skewness0.033052576
Sum782822.16
Variance74.56632
MonotonicityNot monotonic
2024-09-29T20:18:52.332098image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3.208001709 382
 
0.7%
3.2 359
 
0.7%
3.223999023 357
 
0.7%
3.176000977 328
 
0.6%
3.247998047 290
 
0.6%
3.255999756 286
 
0.5%
3.264001465 275
 
0.5%
3.288000488 244
 
0.5%
3.335998535 228
 
0.4%
3.167999268 219
 
0.4%
Other values (27360) 45119
86.1%
(Missing) 4326
 
8.3%
ValueCountFrequency (%)
0 1
< 0.1%
0.4239990234 1
< 0.1%
2.976000977 1
< 0.1%
2.984696145 1
< 0.1%
2.999495604 1
< 0.1%
3.008001709 1
< 0.1%
3.015997314 2
< 0.1%
3.040002441 2
< 0.1%
3.047998047 1
< 0.1%
3.092335761 1
< 0.1%
ValueCountFrequency (%)
80.99927861 1
 
< 0.1%
78.62512794 1
 
< 0.1%
32.56863598 1
 
< 0.1%
32.51999512 2
< 0.1%
32.51566854 1
 
< 0.1%
32.48000488 1
 
< 0.1%
32.41892155 1
 
< 0.1%
32.39200439 3
< 0.1%
32.38775219 1
 
< 0.1%
32.38773751 1
 
< 0.1%

Interactions

2024-09-29T20:18:48.495417image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-09-29T20:18:32.788953image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-09-29T20:18:33.895852image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-09-29T20:18:34.946814image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-09-29T20:18:35.967972image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-09-29T20:18:36.886836image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-09-29T20:18:37.876740image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-09-29T20:18:38.931965image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-09-29T20:18:39.977851image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-09-29T20:18:41.050118image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-09-29T20:18:42.050491image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-09-29T20:18:43.062958image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-09-29T20:18:44.060156image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-09-29T20:18:45.082502image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-09-29T20:18:47.421552image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-09-29T20:18:48.569341image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-09-29T20:18:32.893586image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-09-29T20:18:33.968445image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-09-29T20:18:35.019761image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-09-29T20:18:36.031025image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-09-29T20:18:36.955040image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
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2024-09-29T20:18:45.011118image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-09-29T20:18:47.350160image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-09-29T20:18:48.419822image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Missing values

2024-09-29T20:18:49.561294image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
A simple visualization of nullity by column.
2024-09-29T20:18:49.716278image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2024-09-29T20:18:49.912287image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

13172_FERM0101.Agitation_PV13172_FERM0101.Air_Sparge_PV13172_FERM0101.Biocontainer_Pressure_PV13172_FERM0101.DO_1_PV13172_FERM0101.DO_2_PV13172_FERM0101.Gas_Overlay_PV13172_FERM0101.Load_Cell_Net_PV13172_FERM0101.pH_1_PV13172_FERM0101.pH_2_PV13172_FERM0101.PUMP_1_PV13172_FERM0101.PUMP_1_TOTAL13172_FERM0101.PUMP_2_PV13172_FERM0101.PUMP_2_TOTAL13172_FERM0101.Single_Use_DO_PV13172_FERM0101.Single_Use_pH_PV13172_FERM0101.Temperatura_PV
DateTime
2023-03-15 00:00:00.0000.00.0480.0NaN0.00.0-6.721.694073-0.8517830.04.960.00.0875.360547800.39199219.376315
2023-03-15 00:15:00.0000.00.0480.0NaN0.00.0-6.721.694073-0.8517830.04.960.00.0875.360547800.39199219.376001
2023-03-15 00:30:00.0000.00.0480.0NaN0.00.0-6.721.694073-0.8517830.04.960.00.0875.360547800.39199219.272022
2023-03-15 00:45:00.0000.00.0480.0NaN0.00.0-6.721.694073-0.8517830.04.960.00.0875.360547800.39199219.271780
2023-03-15 01:00:00.0000.00.0480.0NaN0.00.0-6.721.694073-0.8517830.04.960.00.0875.360547800.39199219.272565
2023-03-15 01:15:00.0000.00.0480.0NaN0.00.0-6.721.694073-0.8517830.04.960.00.0875.360547800.39199219.193671
2023-03-15 01:30:00.0000.00.0480.0NaN0.00.0-6.721.694073-0.8517830.04.960.00.0875.360547800.39199219.217483
2023-03-15 01:45:00.0000.00.0480.0NaN0.00.0-6.721.694073-0.8517830.04.960.00.0875.360547800.39199219.216803
2023-03-15 02:00:00.0000.00.0480.0NaN0.00.0-6.721.694073-0.8517830.04.960.00.0875.360547800.39199219.192596
2023-03-15 02:15:00.0000.00.0480.0NaN0.00.0-6.721.694073-0.8517830.04.960.00.0875.360547800.39199219.112390
13172_FERM0101.Agitation_PV13172_FERM0101.Air_Sparge_PV13172_FERM0101.Biocontainer_Pressure_PV13172_FERM0101.DO_1_PV13172_FERM0101.DO_2_PV13172_FERM0101.Gas_Overlay_PV13172_FERM0101.Load_Cell_Net_PV13172_FERM0101.pH_1_PV13172_FERM0101.pH_2_PV13172_FERM0101.PUMP_1_PV13172_FERM0101.PUMP_1_TOTAL13172_FERM0101.PUMP_2_PV13172_FERM0101.PUMP_2_TOTAL13172_FERM0101.Single_Use_DO_PV13172_FERM0101.Single_Use_pH_PV13172_FERM0101.Temperatura_PV
DateTime
2024-09-10 21:45:00.0000.00.0-0.2980350.00.04.000139-1.441.444136-0.6133040.00.00.00.0799.991992800.11997115.423999
2024-09-10 22:00:00.0000.00.0-0.3564020.00.03.999921-1.441.444136-0.6133040.00.00.00.0799.991992800.11997115.359998
2024-09-10 22:15:00.0000.00.0-0.4169120.00.04.000179-1.441.444136-0.6133040.00.00.00.0799.991992800.11997115.312000
2024-09-10 22:30:00.0000.00.0-0.5433320.00.04.000018-1.441.444136-0.6133040.00.00.00.0799.991992800.11997115.312000
2024-09-10 22:45:00.0000.00.0-0.6221070.00.03.999754-1.441.444136-0.6133040.00.00.00.0799.991992800.11997115.275286
2024-09-10 23:00:00.0000.00.0-0.6795510.00.03.999814-1.441.444136-0.6133040.00.00.00.0799.991992800.11997115.295996
2024-09-10 23:15:00.0000.00.0-0.5815980.00.04.000095-1.441.444136-0.6133040.00.00.00.0799.991992800.11997115.280005
2024-09-10 23:30:00.0000.00.0-0.5675660.00.03.999928-1.441.444136-0.6133040.00.00.00.0799.991992800.11997115.231995
2024-09-10 23:45:00.0000.00.0-0.4867500.00.04.000093-1.441.444136-0.6133040.00.00.00.0799.991992800.11997115.256006
2024-09-11 00:00:00.0000.00.0-0.5794500.00.04.000006-1.441.444136-0.6133040.00.00.00.0799.991992800.11997115.200000

Duplicate rows

Most frequently occurring

13172_FERM0101.Agitation_PV13172_FERM0101.Air_Sparge_PV13172_FERM0101.Biocontainer_Pressure_PV13172_FERM0101.DO_1_PV13172_FERM0101.DO_2_PV13172_FERM0101.Gas_Overlay_PV13172_FERM0101.Load_Cell_Net_PV13172_FERM0101.pH_1_PV13172_FERM0101.pH_2_PV13172_FERM0101.PUMP_1_PV13172_FERM0101.PUMP_1_TOTAL13172_FERM0101.PUMP_2_PV13172_FERM0101.PUMP_2_TOTAL13172_FERM0101.Single_Use_DO_PV13172_FERM0101.Single_Use_pH_PV13172_FERM0101.Temperatura_PV# duplicates
1050NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN4325
8750.00.0480.0NaN0.00.0-5.921.536163-0.6520250.044.6399900.014.304988809.708496800.44799826.28800020
6710.00.0480.0NaN0.00.0-6.081.536163-0.6520250.044.6399900.014.304988809.708496800.44799815.18399713
9220.00.0480.0NaN0.00.0-5.921.536163-0.6520250.044.6399900.014.304988809.708496800.44799827.09599612
2840.00.0480.0NaN0.00.0-6.96-4.6862291.2984980.07.4399990.02.766121736.844434800.20800817.79200411
2970.00.0480.0NaN0.00.0-6.96-4.6862291.2984980.07.4399990.02.766121736.844434800.20800817.99200411
3050.00.0480.0NaN0.00.0-6.96-4.6862291.2984980.07.4399990.02.766121736.844434800.20800818.11999511
6950.00.0480.0NaN0.00.0-6.001.502810-0.6133040.044.6399900.014.304988809.708496800.44799814.51200011
7080.00.0480.0NaN0.00.0-6.001.502810-0.6133040.044.6399900.014.304988809.708496800.44799814.71999511
8770.00.0480.0NaN0.00.0-5.921.536163-0.6520250.044.6399900.014.304988809.708496800.44799826.31999511